How to Fix Mispronounced Names, Numbers and Acronyms in AI Voiceovers

Published on September 16, 2026 by Steven Jones

AI voice pronunciation problems are usually easier to fix when you stop treating the whole script as the problem. A company name, product code, date, or acronym can fail because the speech model interprets the written form differently from how you intended it to sound.

This guide uses a word-level repair process for AI voiceovers: isolate the bad phrase, rewrite only what the narrator needs to say, test the correction several times, then put it back into its original sentence. It covers phonetic spellings, initialisms, acronyms, numbers, product IDs and punctuation without drifting into broad voice quality or accent selection.

Test the corrected line before generating the full script.

Fix pronunciation in this order

Check	What to change	What it fixes	Common side effect
1. Intended reading	Write down exactly how the phrase should sound	Ambiguous names, numbers and abbreviations	You may discover the written form has more than one valid reading
2. Spoken form	Replace the raw text with words or letter names	Initialisms, currency, dates and IDs	The performance script no longer matches the display text
3. Phonetic spelling	Respell only the difficult word	Names and invented brand terms	A heavy-handed spelling can change stress or sound unnatural
4. Punctuation	Add a comma, full stop or short phrase break	Rushed letters and awkward joins	Too much punctuation creates robotic pauses
5. Context test	Put the corrected phrase back into the sentence	Pronunciations that change around neighbouring words	A correction that works alone may still fail in a paragraph

The order matters. Don’t start by changing voice, speed, punctuation, and spelling at the same time. If the next render improves, you will not know which change fixed it. That makes future corrections slower and more expensive.

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Use a four-part before-and-after pronunciation test.

For every problem phrase, keep the test record small: problem phrase – attempted correction – resulting audio – remaining limitation. Generate the shortest line that still contains enough context to expose the error. Once it works, repeat it at least twice before trusting the fix, then test the same wording inside the original sentence.

A useful mixed test line is:

At 9:05, Kairova Labs shipped AX-2047-B. The API call cost £1,249.50 and the ETA is 03/04/2026.

That single line deliberately contains five separate pronunciation decisions: a coined company name, a time, a product identifier, an initialism, currency and an ambiguous numeric date. Repair each one separately, rather than rewriting the entire sentence in one attempt.

Names and brand terms: phonetic spelling is a local fix, not a vocabulary update

For an unfamiliar name, first decide the pronunciation you actually want. If the fictional brand Kairova is intended to sound like “kye-ROH-vuh”, test that spoken approximation in place of the original spelling. Keep the surrounding sentence unchanged.

Then listen for more than the consonants and vowels. Phonetic respelling can move the stress, lengthen a syllable or make the narrator hesitate. If “kye-ROH-vuh” sounds over-enunciated, try a lighter approximation such as “kyrova”. The best input is the least distorted spelling that consistently produces the intended sound.

There is a production trap here: the text that sounds best is not always the text you want on screen. If captions, subtitles or transcripts are created from your input script, a phonetic spelling can leak into the displayed copy. Keep a clean display script and a separate performance script when pronunciation fixes alter the written words.

Acronyms and initialisms need an explicit decision: word or letters?

Do not assume the voice model knows whether a capitalised term should be spoken as a word. NASA is normally spoken as a word; API is normally spoken as individual letters. SQL is a better example of the real problem because both “sequel” and “S Q L” are used. The model can’t reliably infer your house style if both readings are legitimate.

Start with the spoken form you want. For an initialism, try A P I. If the letters run together, test A, P, I or a short phrase break around the term. For an acronym intended as a word, normal word casing can sometimes reduce letter-by-letter delivery, but test it because casing behaviour varies by engine and language.

Hyphens, spaces and punctuation are tokenisation tricks, not universal pronunciation controls. They can help one model and make another voice sound choppy. Once a version works, test the same correction in the full line rather than assuming the isolated result will carry over.

Numbers should be rewritten according to meaning, not appearance

Raw numbers are dangerous because the same characters can represent a quantity, date, version, telephone number or product code. The safest correction is to write the meaning you want spoken.

Written text	Possible spoken input	Why the distinction matters
1,250	one thousand two hundred and fifty	Prevents a model reading it as “twelve fifty”
3.5	three point five	A version number is not automatically “three and a half”
020 7946 0958	zero two zero, seven nine four six, zero nine five eight	Telephone numbers usually need digit-by-digit control
AX-2047-B	A X, two zero four seven, B	Separates letters from the numeric identifier
03/04/2026	3 April 2026	Removes the UK/US date ambiguity
£1,249.50	one thousand two hundred and forty-nine pounds and fifty pence	Makes the currency unit and decimal meaning explicit

This is also where an apparently “correct” pronunciation can change meaning. Reading 3.5 as “three and a half” may be fine for a measurement and wrong for software version 3.5. Never optimise the sound before you have defined the semantic reading.

Punctuation can repair pacing, but it cannot replace pronunciation control

A comma can stop an acronym being glued to the next word. A full stop can force a cleaner reset between a product code and the next sentence. Breaking one long sentence into two can also reduce rushed numbers.

But punctuation is a blunt instrument. If you insert commas between every difficult token, the voiceover starts to sound edited rather than spoken. Use punctuation after you have clarified the word itself, not as the first response to every mispronunciation.

Do not regenerate a full narration to repair one bad line

If 14 words are wrong in a 1,000-word narration, work on those 14 words. Regenerating the whole script can introduce new pronunciation, timing or delivery differences in sections that were already acceptable, while consuming more credits than the repair required.

A better workflow is to generate narration in editable sections from the start. Keep sentence or paragraph boundaries that you can replace cleanly in your audio editor. When one name fails, regenerate the smallest section that can be cut back into the finished voiceover without an obvious change in cadence.

This matters even more when the troublesome term appears repeatedly. Find the correction once, record it in a small pronunciation sheet for the project, then reuse the same performance spelling. Do not rely on memory across ten scripts.

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When script-level fixes are no longer enough

Some speech platforms expose dedicated pronunciation controls. Microsoft’s SSML pronunciation documentation, for example, describes phoneme, custom lexicon, say-as and substitution controls. Those features are provider-specific and should not be assumed to exist in every web TTS tool.

DIY AI Studio currently takes a simpler script-first approach: write abbreviations as spoken words, clarify numbers, use punctuation for pauses and spell difficult names phonetically where helpful. It does not currently offer dedicated phoneme dictionaries or SSML controls, so don’t paste markup into Studio expecting it to be interpreted as pronunciation syntax.

If you repeatedly need a controlled vocabulary of hundreds of names, medical terms or product codes, provider-level pronunciation dictionaries may be more efficient than maintaining phonetic substitutions in every script. At that point, the problem has moved from “repair this line” to “choose a TTS system with vocabulary control”. Keep that broader decision on the comparison pages: see our Fish Audio review and Fish Audio vs ElevenLabs comparison.

A reusable pronunciation repair checklist

• Write the intended spoken form before changing the script.
• Isolate the smallest phrase that still reproduces the error.
• Change one variable at a time.
• Spell initialisms as letters and ambiguous numbers as spoken words.
• Use phonetic respelling only for the difficult term.
• Add punctuation only when pacing still needs help.
• Repeat the corrected line to check consistency.
• Test it again inside the original sentence or paragraph.
• Keep display text separate from phonetic performance text.
• Regenerate the smallest editable section, not the entire narration.

The practical rule: fix meaning first, sound second

The fastest pronunciation fixes start by removing ambiguity from the script. Tell the voice engine whether the term is a word or a sequence of letters, whether the number is a date or an identifier, and how an unfamiliar name should sound. Then use punctuation only to shape the delivery.

Most importantly, judge the correction in context. A clean isolated pronunciation is useful, but the version that matters is the one that survives the full sentence without changing meaning, pacing or the surrounding delivery. Test that line first, save the working performance spelling, then move on to the rest of the script.